AI RESEARCH
Differentiable Conformal Training for LLM Reasoning Factuality
arXiv CS.LG
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ArXi:2604.20098v1 Announce Type: new Large Language Models (LLMs) frequently hallucinate, limiting their reliability in critical applications. Conformal Prediction (CP) addresses this by calibrating error rates on held-out data to provide statistically valid confidence guarantees. Recent work extends CP to LLM factuality to filter out risky claims, ensuring that hallucination rates remain below a user-specified level (e.g., 10